Table REF  presents a metric summary between the chosen baselines and benchmarks. It demonstrates that CFA\(_{\text{fixed}}\)  and CFA\(_{\text{grow}}\)  are comparable, or even stronger, in comparison with the current state-of-the-art methods, specially when we take in consideration that CFA\(_{\text{fixed}}\)  presents a fixed memory footprint. Furthermore, both CFA\(_{\text{fixed}}\)  and CFA\(_{\text{grow}}\)  have great BWT and FWT metrics, with CFA\(_{\text{grow}}\)  being the only model providing positive values to all metrics. This means that CFA signalizes some zero-shot learning [1]}, although not explicitly focused here.
